caa a22 4500 606243623 CHVBK 20210128101325.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s11694-014-9200-9 doi (NATIONALLICENCE)springer-10.1007/s11694-014-9200-9 Evaluation of a commercial electronic nose system coupled with universal gas sensing chamber for sensing indicator compounds associated with meat safety [Elektronische Daten] [Punyatoya Mohapatra, Suranjan Panigrahi, Jayendra Amamcharla] This study was conducted to evaluate the performance of a commercial electronic nose (Cyranose 320™) for sensing indicator compounds (ethanol and acetic acid) associated with spoiled beef. The present study reported the sensitivity of an array of 32 sensors to ethanol and acetic acid. Different vapor concentrations of ethanol (37, 100, 250 and 500ppm) and acetic acid (38, 75, 100, 200 and 300ppm) were tested to evaluate the performance of the commercial system. An in-house designed universal gas sensing and characterization system was coupled with the electronic nose system to generate the desired gas concentration. The raw smell print patterns were obtained and analyzed for individual and multiple detectors. Tukey's multiple comparison technique was performed to analyze the response of individual detectors. Area above and below the baseline were selected as two features for pair wise comparison of the detectors. Different sensors showed different responses between various concentrations of gases. Analysis of multiple detectors was performed using linear and quadratic discriminant analysis (LDA and QDA) along with bootstrap. LDA along with bootstrap provided thehighest totalclassification accuracies of 94.34% between 100 and 200ppm of acetic acid. QDA provided higher totalclassification accuracy of 89.69% at lower concentration level of 38 and 75ppm for acetic acid and 84.78% between 37 and 100ppm of ethanol. Hence, QDA was a better model of choice at lower concentrations. This study proved non-selective nature of sensors and showed that simultaneous use of multiple sensor information provided better classification accuracy for discriminating various gas concentrations as compared to usingindividual sensor output. Springer Science+Business Media New York, 2014 Electronic nose nationallicence Universal gas sensing and characterization system nationallicence Cyranose 320™ nationallicence Conducting polymers nationallicence Sensor nationallicence Ethanol nationallicence Acetic acid nationallicence Mohapatra Punyatoya Department of Agricultural and Biosystems Engineering, North Dakota State University, 58102, Fargo, ND, USA aut Panigrahi Suranjan Department of Agricultural and Biosystems Engineering, North Dakota State University, 58102, Fargo, ND, USA aut Amamcharla Jayendra Animal Science and Industry, Kansas State University, 232 Weber hall, 66506-8028, Manhattan, KS, USA aut Journal of Food Measurement and Characterization Springer US; http://www.springer-ny.com 9/2(2015-06-01), 121-129 2193-4126 9:2<121 2015 9 11694 https://doi.org/10.1007/s11694-014-9200-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11694-014-9200-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mohapatra Punyatoya Department of Agricultural and Biosystems Engineering, North Dakota State University, 58102, Fargo, ND, USA aut NATIONALLICENCE 700 1- Panigrahi Suranjan Department of Agricultural and Biosystems Engineering, North Dakota State University, 58102, Fargo, ND, USA aut NATIONALLICENCE 700 1- Amamcharla Jayendra Animal Science and Industry, Kansas State University, 232 Weber hall, 66506-8028, Manhattan, KS, USA aut NATIONALLICENCE 773 0- Journal of Food Measurement and Characterization Springer US; http://www.springer-ny.com 9/2(2015-06-01), 121-129 2193-4126 9:2<121 2015 9 11694